With the exponential growth of big data over the past few years, the need for data scientists becomes more and more pronounced and urgent.
The Data Science Institute at Saint Peter’s University is training the next generation of Data Science students offering a cutting-edge academic STEM program to meet such demands and train the next generation of data scientists. The Institute works closely with industry thought leaders to bring innovative ideas to market.
The Data Science program integrates scientific methods from statistics, computer science, and data-based business management to extract knowledge from data and drive decision making. Our curriculum provides students with a rigorous course of study in big data technologies, applications, and practices a pathway for student internships and full-time employment. Graduates are prepared to meet the challenges at the intersection between big data, business analytics, and other emerging fields.
In addition to the Masters's program, we offer customized certificate and training courses in the field of analytics. One semester preparatory courses are designed for graduate students and tailored for international studies.
At A Glance
Degree Awarded: Master of Science in Data Science
Course Locations: Jersey City Campus
Program Duration: 36 Credits: A full‐time student taking 24 credits/year should complete in 1.5 years.
Course Format: Classes meet in person Monday to Friday during the day or during the evening.
Accelerated BS to MS in Data Science Program
You can earn your undergraduate degree and an MS in Data Science in five years through our Accelerated Program.
Data Science is the discipline that integrates scientific methods from statistics, computer science, and business management to extract knowledge from data to drive decision making. This program is designed for students with a background in computer science, applied science, business, or economics. For preparedness, students need to be currently enrolled in a BS program.
Introduction to Data Science
Data Analysis and Decision Modeling
Database and Data Warehousing
Big Data Analytics
Predictive Analytics and Experimental Design
Data Law, Ethics and Privacy
Capstone: Business Analytics
Total program credits: 36
The Data Science program will be offered on a semester schedule and is designed for both full-time and part-time study.
The degree requires 36 semester-hour credits. A capstone course is required and will be taken in the final semester of coursework.
As of January 1, 2016, completion of an internship related to Data Science is required for all students except those who have 3+ years of professional work experience; those with full-time employment during the length of the program; and those who are participating in the exchange program. The graduate internship can start in the first semester of classes. Please consult your program advisor to determine if it is possible to obtain a waiver.
Saint Peter’s University assigns an academic advisor to every candidate.
Students are expected to enroll continuously until their programs are completed. Students are required to maintain satisfactory academic progress by maintaining the required grade point average and accumulating sufficient credits within the stipulated time frame of five years.
Develop a depth understanding of the key technologies in data science and business analytics: data mining, machine learning, visualization techniques, predictive modeling, and statistics.
Practice problem analysis and decision-making.
Gain practical, hands-on experience with statistics programming languages and big data tools through coursework and applied research experiences.
Students who have completed the MS in Data Science and Business Analytics Program will be able to:
Apply quantitative modeling and data analysis techniques to the solution of real-world business problems, communicate findings, and effectively present results using data visualization techniques.
Recognize and analyze ethical issues in business related to intellectual property, data security, integrity, and privacy.
Apply ethical practices in everyday business activities and make well-reasoned ethical business and data management decisions.
Demonstrate knowledge of statistical data analysis techniques utilized in business decision-making.
Apply principles of Data Science to the analysis of business problems.
Use data mining software to solve real-world problems.
Employ cutting-edge tools and technologies to analyze Big Data.
Apply algorithms to build machine intelligence.
Demonstrate use of teamwork, leadership skills, decision making, and organization theory.